1 Introduction and main results
In
$2019$
, R. Gross [Reference Gross9] posed the following problem. Given a nondegenerate distribution
$\mu $
with zero mean and finite second moment, find a simply connected domain U such that if
$(Z_{t})_{t\geq 0}$
is a planar Brownian motion started at
$0$
and
$\tau _{U}$
is its exit time from U, then
$\Re (Z_{\tau _{U}})$
has the law
$\mu $
.
This is called the planar (or conformal) Skorokhod embedding problem (PSEP). Gross gave a constructive solution using the principle of conformal invariance of planar Brownian motion [Reference Revuz and Yor11]. The domain he constructed enjoys the property that its underlying exit time has a finite average. In [Reference Boudabra and Markowsky3], Boudabra and Markowsky showed that Gross’ approach remains valid if the distribution
$\mu $
has a finite pth moment for some
$p>1$
. They reformulated the problem by requiring the finiteness of
$\mathbb {E}(\tau _{U}^{{p}/{2}})$
. We adopt this formulation in this note. Later on, in a subsequent work [Reference Boudabra and Markowsky2], the same authors provided a second solution to the PSEP with a different geometry from Gross’ domain. Both solutions start by crafting a certain univalent function acting on the open unit disc
$\mathbb {D}$
. Then, the authors show that the range U of such a function fits the statistical requirement
$\Re (Z_{\tau _{U}})\sim \mu $
. Our main result gives a sufficient condition for the existence of a
$p=1$
embedding in terms of the Hilbert transform of the quantile function (see Theorem 1.4). Through this work, the following notation is adopted.
-
• $\mathbb {D}$
: the open unit disc in the plane. -
• $\mathbb {T}$
: the unit circle in the plane. -
• $L_{2\pi }^{p}$
(
$p>0$
): the space of real valued
$2\pi $
-periodic functions f such that $$ \begin{align*} \Vert f\Vert_{p}=\bigg(\frac{1}{2\pi}\int_{0}^{2\pi}\vert f(t)\vert^{p}\,dt\bigg)^{{1}/{p}} \end{align*} $$is finite; we write $L^{p}(\mathbb {T})$
for the space of complex-valued functions on
$\mathbb {T}$
.
-
• Standard planar Brownian motion: planar Brownian motion started at $0$
.
The ingredients in the proofs of the results are Hardy spaces and the Hilbert transform. We recall their definitions for the reader’s convenience.
Definition 1.1. Let f be an analytic function in the unit disc. The pth Hardy norm of f is defined by
The set of analytic functions on
$\mathbb {D}$
with finite
$\boldsymbol {H}^{p}$
norm is denoted by
$\boldsymbol {H}^{p}(\mathbb {D})$
and is called the Hardy space (of index p).
Definition 1.2. The Hilbert transform of a
$2\pi $
-periodic function f is defined by
where
$PV$
denotes the Cauchy principal value. Note that the Hilbert transform is an anti-involution on zero-mean functions, that is,
$\mathcal {H}^{2}=-\mathrm {id}$
. The Hilbert transform exists almost everywhere (a.e.) for any function
$f\in L^{p}(\mathbb {T})$
with
$p\geq 1$
. In addition, if
$p>1$
, then
for some positive constant
$\lambda _{p}$
(see [Reference Duren5]).
The main results of our work are the following theorems.
Theorem 1.3. Let f be a univalent function on
$\mathbb {D}$
with
$f(0)=0$
and set
$U=f(\mathbb {D})$
. Let
$(Z_{t})_{t\geq 0}$
be standard planar Brownian motion and
$\tau _{U}$
its exit time from U. Then,
$Z_{\tau _{U}}$
and
$f(\xi )$
share the same distribution where
$\xi $
is any random variable uniformly distributed on the unit circle and
$f(\xi )$
denotes the radial boundary value of f at
$\xi $
(defined a.e.).
Theorem 1.4. Assume
$\mu $
is a nondegenerate probability measure with zero mean and let q be its quantile function. Then, there exists a simply connected domain
$U\subset \mathbb {C}$
containing the origin such that, for a standard planar Brownian motion
$(Z_{t})_{t\ge 0}$
and
$\tau _{U}:=\inf \{t\ge 0:Z_{t}\notin U\}$
,
whenever
$\mathcal {H}\{q({\vert \cdot \vert }/{\pi })\}\in L_{2\pi }^{1}$
.
2 Proofs
Before proving our main results, we recall two celebrated results that we need in the proof.
Theorem 2.1 [Reference Duren6, Theorem 3.16].
Any univalent function acting on the unit disc belongs to the Hardy space
$\boldsymbol {H}_{p}(\mathbb {D})$
for all
$p<\tfrac 12$
.
Theorem 2.2 [Reference Rudin12].
If
$f\in \boldsymbol {H}_{p}(\mathbb {D})$
for some positive p, then:
-
(1) the radial limit of f, say $f^{\ast }(\xi )$
, exists a.e. on
$\mathbb {T}$
and
$f^{*}\in L^{p}(\mathbb {T})$
; -
(2) ${\lim }_{r\rightarrow 1^{-}}\Vert f(r\cdot )-f^{*}\Vert _{p}=0$
; -
(3) $\Vert f^{*}\Vert _{p}$
equals the pth Hardy norm of f.
From now on, we do not distinguish notationally between a Hardy function and its boundary values;
$f(\xi )$
will denote the radial limit on
$\mathbb {T}$
.
Proof of Theorem 1.3.
The proof is adapted from [Reference Boudabra and Markowsky3, Lemma 3.2]. The main difference is that in [Reference Boudabra and Markowsky3], the authors required that f belongs to the Hardy space
$\boldsymbol {H}_{p}(\mathbb {D})$
for some
$p>1$
, while this constraint is dropped here.
Let
$(W_{t})_{t}$
be a standard planar Brownian motion killed on exiting
$\mathbb {D}$
. By the conformal invariance principle, the planar process
$(Z_{t}=f(W_{\sigma ^{-1}(t)}))_{t\geq 0}$
is a standard planar Brownian motion, where
$\sigma $
is the time change given by
In particular,
where
$\tau _{n}$
denotes the exit time of
$W_{t}$
from
$\mathbb {D}_{n}:=(1-{1}/{n})\mathbb {D}$
. In fact,
$\sigma (\tau _{n})$
is the exit time of
$(Z_{t})_{t\geq 0}$
from
$f(\mathbb {D}_{n}).$
Since
$\mathbb {D}_{n}\uparrow \mathbb {D}$
as
$n\rightarrow +\infty $
, we have
$\tau _{n}\uparrow \tau _{\mathbb {D}}$
almost surely (a.s.). By continuity of the time change,
$\sigma (\tau _{n})$
converges to
$\sigma (\tau _{\mathbb {D}})$
a.s. The quantity
$\sigma (\tau _{\mathbb {D}})$
is exactly the exit time of
$(Z_{t})_{t\geq 0}$
from U, which we denote by
$\tau _{U}$
. As the Brownian path is continuous a.s.,
$Z_{\sigma (\tau _{n})}$
converges to
$Z_{\tau _{U}}$
a.s. On an auxiliary probability space
$\Omega =(0,2\pi )$
equipped with the normalised Lebesgue measure, define
$\xi _{n}(\omega )=(1-{1}/{n})e^{\omega i}$
and
$\xi (\omega )=e^{\omega i}$
, where
$\omega \in \Omega $
. As planar Brownian motion is isotropic, the two random variables
$W_{\tau _{n}}$
and
$\xi _{n}(\omega )=(1-{1}/{n})e^{\omega i}$
share the same distribution. In particular,
$f(\xi _{n})$
and
$Z_{\sigma (\tau _{n})}$
have the same law. Now, fix
$p\in (0,\tfrac 12)$
. By Theorem 2.1, f belongs to
$\boldsymbol {H}_{p}(\mathbb {D})$
and, hence, it extends radially to the boundary of
$\mathbb {D}$
. We have
By the second point of Theorem 2.2,
$\mathbb {E}(\vert f(\xi _{n})-f(\xi )\vert ^{p})$
converges to zero. Hence,
$f(\xi _{n})$
converges to
$f(\xi )$
in distribution. As
$f(\xi _{n})$
and
$Z_{\sigma (\tau _{n})}$
are equal in distribution,
$Z_{\sigma (\tau _{n})}$
converges to
$f(\xi )$
in distribution as well. However,
Therefore,
$Z_{\tau _{U}}$
and
$f(\xi )$
have the same distribution by uniqueness of weak limits. This ends the proof.
Proof of Theorem 1.4.
Recall that the quantile function q of
$\mu $
is simply the pseudo-inverse of the cumulative distribution function (c.d.f) F of
$\mu $
. More precisely,
A crucial property of q is that if q is fed with a uniformly distributed random variable X in
$(0,1)$
, then
$q(X)$
samples as
$\mu $
. Set
$\varphi (\theta )=q({\vert \theta \vert }/{\pi })$
with
$\theta \in (-\pi ,\pi )$
.
The assumption
$H\{\varphi \}\in L_{2\pi }^{1}$
implies that the analytic map
The map G is the standard Cauchy–Poisson integral (see [Reference Duren5, Ch. 3]). In particular,
Furthermore, the map
$G(z)$
is univalent by [Reference Gross9, Proposition 2.2]. In particular,
${U:=G(\mathbb {D})}$
is simply connected and contains the origin. Run a planar Brownian motion
$(Z_{t})_{t}$
inside U and set
$\tau _{U}$
as the exit time of
$Z_{t}$
from U. By (2.1), the boundary value of G has real part
$\varphi $
, which encodes the quantile of
$\mu $
. Therefore, by Theorem 1.3,
Since
$G\in \boldsymbol {H}^{1}(\mathbb {D})$
, Burkholder’s characterisation of the finiteness of the moments of
$\tau _{U}$
[Reference Burkholder4] yields
$\mathbf {E}(\tau _{U}^{{1}/{2}})<+\infty $
. Therefore, the PSEP is solvable.
3 Comments
3.1 Comment 1
Theorem 1.3 might seem obvious as one may think that
is immediate. However, this is not obvious for the simple reason that
$W_{\tau _{n}}$
does not approach the boundary of the unit disc radially! Theorem 1.4 naturally raises the converse question: if the PSEP is solvable for a given law
$\mu $
, must the Hilbert transform
$\mathcal {H}\{q({\vert \cdot \vert }/{\pi })\}\in L_{2\pi }^{1}$
? We conjecture that the answer is yes.
3.2 Comment 2
Theorem 1.4 implies the existence of solutions for the PSEP when
$\mu $
has a finite pth moment for some
$p>1$
. This follows from (1.1).
A natural question is how to find functions with integrable Hilbert transforms in
$L_{2\pi }^{1}$
. A naive way to do so is to compute the Hilbert transform and then check its integrability. However, this is hard in practice. The following result, due to Zygmund, is handy.
Theorem 3.1 (see [Reference Duren5, Ch. 4]).
Let u be a harmonic function in the unit disc such that
Then,
In particular, the condition (3.1) is, in some sense, the weakest that one can impose on u. Note that the
$\log ^{+}(x)$
can be replaced by
$\log (1+\vert x\vert )$
[Reference Garnett8]. A classical result in harmonic analysis says that if g is a convex function, then
$g(u)$
is subharmonic. In particular, the integral in (3.1) is nondecreasing in r [Reference Rudin12]. So, in terms of the boundary function, the condition (3.1) can be replaced by
which was originally formulated. Based on this fact, the planar Skorokhod embedding problem becomes solvable once
$\vert \varphi \vert \!\log ^{+}(\vert \varphi \vert )$
belongs to
$L_{2\pi }^{1}$
.
Next, we provide an example where the distribution
$\mu $
has only a first moment. Consider the distribution of the random variable
with X uniformly distributed on
$(0,1)$
. The underlying quantile function is
Using Bertrand’s criterion for integrals, q belongs to
$L^{p}$
for
$p=1$
, but not for any higher p. Near zero, we have the approximation
Thus, the integral of
$\vert q\vert \!\log ^{+}(\vert q\vert )$
is finite. Therefore, the Hilbert transform of
$\varphi $
is in
$L_{2\pi }^{1}$
(recall
$\varphi (\theta )=q({\vert \theta \vert }/{\pi })$
). Consequently, the Skorokhod embedding problem is solvable for this
$\mu $
.
Remark 3.2. Gross’ construction of the map
$G(z)$
is based on the calculation of the Fourier coefficients of
$\varphi $
. Now, one can see that
$G(z)$
can be simply expressed as
Although this paper is primarily addressing the method introduced in [Reference Gross9], the approach is directly applicable, without modification, to the method described in [Reference Boudabra and Markowsky2].
3.3 Comment 3
Mathematicians tend to shy away from
$L^{p}$
spaces when
$p<1$
due to their unconventional properties, such as the failure of the triangle inequality, or, in relation to our context, the inability to construct Poisson integrals. However, we present an example that shows something might be done when
$p<1$
. Using the formulae in [Reference Boudabra1, Reference Boudabra and Markowsky3], the c.d.f of the stopped planar Brownian motion upon leaving the Koebe domain
$\mathcal {K}=\mathbb {C}-(-\infty ,-\tfrac 14]$
is given by
for
$w\in (-\infty ,-\tfrac 14]$
. That is,
Interestingly, the function
$\varphi (t)$
coincides with the real part of the radial limit of the Koebe function
$k(z)={z}/{(1-z)^{2}}$
. In [Reference Gardiner, Aikawa, Kumagai, Mizuta and Suzuki7], the author gathered some results about the existence of entire functions and harmonic functions with a predefined radial boundary function. The following natural question seems worth being addressed. How can we construct the univalent function whose real part of its radial limit matches
$\varphi $
when the distribution
$\mu $
has exclusively a finite pth moment for some
$p<1$
? Another related issue will be how to reconcile this with the fact that every univalent function belongs to
$\boldsymbol {H}^{p}(\mathbb {D})$
for all
$p<\tfrac 12$
?
3.4 Comment 4
It is worth noting that Theorem 1.3 is still valid if f is a proper map or, more generally, a B-proper map. The notion of B-properness was introduced in [Reference Markowsky10]. Both types of functions ensure that if a sequence
$(z_{n})_{n}$
in the input domain is approaching its boundary, then the image sequence
$(f(z_{n}))_{n}$
is also approaching the boundary of the range of f.
Acknowledgement
I would like to thank Professor Zihua Guo from Monash University for his valuable comments.


